Bernhard Lehner
Bernhard Lehner
Post-Doc at the Institute of Computational Perception, JKU Linz, Austria
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Zitiert von
Zitiert von
CP-JKU submissions for DCASE-2016: A hybrid approach using binaural i-vectors and deep convolutional neural networks
H Eghbal-Zadeh, B Lehner, M Dorfer, G Widmer
IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and …, 2016
On the reduction of false positives in singing voice detection
B Lehner, G Widmer, R Sonnleitner
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
Acoustic scene classification with fully convolutional neural networks and I-vectors
M Dorfer, B Lehner, H Eghbal-zadeh, H Christop, P Fabian, W Gerhard
DCASE2018 Challenge, 2018
A low-latency, real-time-capable singing voice detection method with LSTM recurrent neural networks
B Lehner, G Widmer, S Bock
2015 23rd European signal processing conference (EUSIPCO), 21-25, 2015
I-Vectors for Timbre-Based Music Similarity and Music Artist Classification.
H Eghbal-Zadeh, B Lehner, M Schedl, G Widmer
ISMIR, 554-560, 2015
Towards Light-Weight, Real-Time-Capable Singing Voice Detection.
B Lehner, R Sonnleitner, G Widmer
ISMIR 2013, 1-6, 2013
A hybrid approach with multi-channel i-vectors and convolutional neural networks for acoustic scene classification
H Eghbal-zadeh, B Lehner, M Dorfer, G Widmer
2017 25th European Signal Processing Conference (EUSIPCO), 2749-2753, 2017
Classifying short acoustic scenes with I-vectors and CNNs: Challenges and optimisations for the 2017 DCASE ASC task
B Lehner, H Eghbal-Zadeh, M Dorfer, F Korzeniowski, K Koutini, ...
DCASE2017 Challenge, 2017
Cross-Version Singing Voice Detection in Classical Opera Recordings.
C Dittmar, B Lehner, T Prätzlich, M Müller, G Widmer
ISMIR, 618-624, 2015
Online, loudness-invariant vocal detection in mixed music signals
B Lehner, J Schlüter, G Widmer
IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (8), 1369 …, 2018
Zero-Mean Convolutions for Level-Invariant Singing Voice Detection.
J Schlüter, B Lehner
ISMIR, 321-326, 2018
An introduction to signal processing for singing-voice analysis: High notes in the effort to automate the understanding of vocals in music
EJ Humphrey, S Reddy, P Seetharaman, A Kumar, RM Bittner, ...
IEEE Signal Processing Magazine 36 (1), 82-94, 2018
Monaural Blind Source Separation in the Context of Vocal Detection.
B Lehner, G Widmer
ISMIR, 309-315, 2015
Acoustic scene classification with reject option based on resnets
B Lehner, K Koutini, C Schwarzlmüller, T Gallien, G Widmer
Proceedings of the Detection and Classification of Acoustic Scenes and …, 2019
Improving voice activity detection in movies
B Lehner, G Widmer, R Sonnleitner
Sixteenth Annual Conference of the International Speech Communication …, 2015
Deep learning approaches for thermographic imaging
P Kovács, B Lehner, G Thummerer, G Mayr, P Burgholzer, M Huemer
Journal of Applied Physics 128 (15), 155103, 2020
A hybrid approach for thermographic imaging with deep learning
P Kovács, B Lehner, G Thummerer, G Mayr, P Burgholzer, M Huemer
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
Uncertainty estimation for non-destructive detection of material defects with u-nets
B Lehner, T Gallien
Proceedings of the 2nd International Conference on Advances in Signal …, 2020
Uncertainty Estimation for Deep Learning-based Thermographic Imaging
B Lehner, T Gallien, P Kovács, G Thummerer, G Mayr, P Burgholzer, ...
Sensors & Transducers 249 (2), 25-35, 2021
Detecting the Presence of Singing Voice in Mixed Music Signals/submitted by Bernhard Lehner
B Lehner
Universität Linz, 2018
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